// Python 集成模块
// 处理与 OpenCV 和 dlib 的交互

// Python 对象包装器
struct PythonCV2 {
  cv2 : @python.PyObject
}

struct PythonDlib {
  dlib : @python.PyObject
  detector : @python.PyObject
  predictor : @python.PyObject
}

struct PythonCamera {
  cap : @python.PyObject
  writer : @python.PyObject?
}

// 初始化 OpenCV
fn init_cv2() -> PythonCV2? {
  try {
    let cv2 = @python.import("cv2")
    Some({ cv2 })
  } catch {
    _ => None
  }
}

// 初始化 dlib
fn init_dlib(model_path : String) -> PythonDlib? {
  try {
    let dlib = @python.import("dlib")
    let detector = @python.call(dlib, "get_frontal_face_detector", [])
    let predictor = @python.call(dlib, "shape_predictor", [model_path])
    Some({ dlib, detector, predictor })
  } catch {
    _ => None
  }
}

// 初始化摄像头
fn init_camera(cv2 : PythonCV2, device_id : Int, width : Int, height : Int) -> PythonCamera? {
  try {
    let cap = @python.call(cv2.cv2, "VideoCapture", [device_id])
    
    // 设置分辨率
    @python.call(cap, "set", [@python.call(cv2.cv2, "CAP_PROP_FRAME_WIDTH", []), width])
    @python.call(cap, "set", [@python.call(cv2.cv2, "CAP_PROP_FRAME_HEIGHT", []), height])
    
    // 检查摄像头是否打开
    let is_opened = @python.call(cap, "isOpened", [])
    if @python.to_bool(is_opened) {
      Some({ cap, writer: None })
    } else {
      None
    }
  } catch {
    _ => None
  }
}

// 初始化视频写入器
fn init_video_writer(cv2 : PythonCV2, filename : String, width : Int, height : Int, fps : Double) -> @python.PyObject? {
  try {
    let fourcc = @python.call(cv2.cv2, "VideoWriter_fourcc", ['X', 'V', 'I', 'D'])
    let writer = @python.call(cv2.cv2, "VideoWriter", [filename, fourcc, fps, (width, height)])
    Some(writer)
  } catch {
    _ => None
  }
}

// 读取摄像头帧
fn read_frame(camera : PythonCamera) -> (@python.PyObject, Bool) {
  try {
    let result = @python.call(camera.cap, "read", [])
    let ret = @python.get_item(result, 0)
    let frame = @python.get_item(result, 1)
    (frame, @python.to_bool(ret))
  } catch {
    _ => (@python.none(), false)
  }
}

// 检测人脸和关键点
fn detect_faces_and_landmarks(dlib_obj : PythonDlib, cv2 : PythonCV2, frame : @python.PyObject) -> Array[@python.PyObject] {
  try {
    // 转换为灰度图
    let gray = @python.call(cv2.cv2, "cvtColor", [frame, @python.call(cv2.cv2, "COLOR_BGR2GRAY", [])])
    
    // 检测人脸
    let faces = @python.call(dlib_obj.detector, "__call__", [gray])
    
    let mut landmarks_list : Array[@python.PyObject] = []
    
    // 对每个人脸预测关键点
    let faces_iter = @python.iter(faces)
    while true {
      match @python.next(faces_iter) {
        Some(face) => {
          let landmarks = @python.call(dlib_obj.predictor, "__call__", [gray, face])
          landmarks_list.push(landmarks)
        }
        None => break
      }
    }
    
    landmarks_list
  } catch {
    _ => []
  }
}

// 绘制关键点
fn draw_landmarks_on_frame(cv2 : PythonCV2, frame : @python.PyObject, landmarks_list : Array[@python.PyObject]) -> @python.PyObject {
  try {
    let mut result_frame = @python.call(frame, "copy", [])
    
    for landmarks in landmarks_list {
      // 绘制81个关键点
      for i in 0..<81 {
        let point = @python.call(landmarks, "part", [i])
        let x = @python.get_attr(point, "x")
        let y = @python.get_attr(point, "y")
        
        @python.call(cv2.cv2, "circle", [result_frame, (@python.to_int(x), @python.to_int(y)), 2, (0, 255, 0), -1])
      }
    }
    
    result_frame
  } catch {
    _ => frame
  }
}